Research on an Intelligent Algorithm for the Restoration of Fractured Aero Engine Wheel Disks

Purpose: To address the challenges of repairing and splicing fragmented aero-engine wheel disks, a composite methodology integrating digital geometric analysis and image registration is proposed. Design/Methodology/Approach: Firstly, the fragment foreground is extracted using the GrabCut algorithm. Contour digitization is achieved by combining the Canny operator with the three-point circle method. The rotation array is optimized using an adaptive step-size algorithm. Vertex grouping is dynamically performed via spectral clustering to complete the simulation repair of disks. Secondly, the eight-neighborhood algorithm is used to extract the fragment profile. The feature contours are screened based on circularity, area, and centroid distance. Sub-pixel ellipse fitting is implemented, and the left fragment is aligned to the right through affine transformation. Inner and outer contours are processed separately to compensate for deformation. Findings: Experiments show that the method successfully splices the main fragments, accounting for more than 85% of the area in the simulated repair stage, and solves difficulties such as deformation, adhesion, and background interference. In damage detection, the defect quantification method based on two-color spatial analysis and KD tree nearest neighbor search can automatically identify the V/U/flat-bottom/inverted trumpet profile morphology. This provides critical spatial parameters and process decision support for practical repair operations, including laser cladding or precision machining. Originality: The study provides both a theoretical foundation and technical validation for the intelligent maintenance of key aero-engine components.